检测像素是否为红色

Question

我们可以定义HSV中红色的范围如下。我想检测某个像素是否为红色？我怎样才能在 Python 中做到这一点？我花了一整天，但无法找到解决方案。请解决我的问题。我是 Python 的新手。我使用的代码是：

img=cv2.imread("img.png")
img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# lower mask (0-10)
lower_red = np.array([0,50,50])
upper_red = np.array([10,255,255])
mask0 = cv2.inRange(img_hsv, lower_red, upper_red)

# upper mask (170-180)
lower_red = np.array([170,50,50])
upper_red = np.array([180,255,255])
mask1 = cv2.inRange(img_hsv, lower_red, upper_red)
image_height,image_width,_=img.shape    
for i in range(image_height):
   for j in range(image_width):
       if img_hsv[i][j][1]>=lower_red and img_hsv[i][j][1]<=upper_red:
          print("Found red")

Answer 1

你几乎是对的。您可以将较低红色和较高红色的蒙版合并为一个蒙版。

为此ColorChecker.png:

我找到红色的步骤：

Read the image and convert to hsv.

I choose the red ranges (lower 0~5, upper 175~180) using this colormap:

Then merge the masks, you can judge whether the pixel is red or not by the mask. Or "crop" the region(s) for visualization:

#!/usr/bin/python3
# 2018.07.08 10:39:15 CST
# 2018.07.08 11:09:44 CST
import cv2
import numpy as np
## Read and merge
img = cv2.imread("ColorChecker.png")
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

## Gen lower mask (0-5) and upper mask (175-180) of RED
mask1 = cv2.inRange(img_hsv, (0,50,20), (5,255,255))
mask2 = cv2.inRange(img_hsv, (175,50,20), (180,255,255))

## Merge the mask and crop the red regions
mask = cv2.bitwise_or(mask1, mask2 )
croped = cv2.bitwise_and(img, img, mask=mask)

## Display
cv2.imshow("mask", mask)
cv2.imshow("croped", croped)
cv2.waitKey()

Choosing the correct upper and lower HSV boundaries for color detection with`cv::inRange` (OpenCV)

检测像素是否为红色

Detect whether a pixel is red or not

python

numpy

opencv

image-processing

hsv